Exploration Of Advances In Statistical Methodologies For Crash Count And Severity Prediction Models

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Exploration of Advances in Statistical Methodologies for Crash Count and Severity Prediction Models

Author : Kai Wang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)

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Book Synopsis Exploration of Advances in Statistical Methodologies for Crash Count and Severity Prediction Models by : Kai Wang

Download or read book Exploration of Advances in Statistical Methodologies for Crash Count and Severity Prediction Models written by Kai Wang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This report first describes the use of different copula based models to simultaneously estimate the two crash indicators: injury severity and vehicle damage. The Gaussian copula model outperforms the other copula based model specifications (i.e. Gaussian, Farlie-Gumbel-Morgenstern (FGM), Frank, Clayton, Joe and Gumbel copula models), and the results indicate that injury severity and vehicle damage are highly correlated, and the correlations between injury severity and vehicle damage varied with different crash characteristics including manners of collision and collision types. This study indicates that the copula-based model can be considered to get a more accurate model structure when simultaneously estimating injury severity and vehicle damage in crash severity analyses. The second part of this report describes estimation of cluster based SPFs for local road intersections and segments in Connecticut using socio-economic and network topological data instead of traffic counts as exposure. The number of intersections and the total local roadway length were appropriate to be used as exposure in the intersection and segment SPFs, respectively. Models including total population, retail and non-retail employment and average household income are found to be the best both on the basis of model fit and out of sample prediction. The third part of this report describes estimation of crashes by both crash type and crash severity on rural two-lane highways, using the Multivariate Poisson Lognormal (MVPLN) model. The crash type and crash severity counts are significantly correlated; the standard errors of covariates in the MVPLN model are slightly lower than the other two univariate crash prediction models (i.e. Negative Binomial model and Univariate Poisson Lognormal model) when the covariates are statistically significant; and the MVPLN model outperforms the UPLN and NB models in crash count prediction accuracy. This study indicates that when simultaneously predicting crash counts by crash type and crash severity for rural two-lane highways, the MVPLN model should be considered to avoid estimation error and to account for the potential correlations among crash type counts and crash severity counts.

Advanced Statistical Modeling of the Frequency and Severity of Traffic Crashes on Rural Highways

Author : Irfan Uddin Ahmed
Publisher :
ISBN 13 :
Total Pages : 222 pages
Book Rating : 4.4/5 (387 download)

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Book Synopsis Advanced Statistical Modeling of the Frequency and Severity of Traffic Crashes on Rural Highways by : Irfan Uddin Ahmed

Download or read book Advanced Statistical Modeling of the Frequency and Severity of Traffic Crashes on Rural Highways written by Irfan Uddin Ahmed and published by . This book was released on 2022 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary objective of practitioners working on traffic safety is to reduce the number and severity of crashes. The Highway Safety Manual (HSM) provides practitioners with analytical tools and techniques to estimate the expected crash frequency and severity with the aim to identify and evaluate safety countermeasures. Expected crash frequency can be estimated using Safety Performance Functions (SPFs) provided in Part C of the HSM. The HSM provides simple SPFs which are developed using the most frequently used crash counts model, the negative binomial regression model. The rural nature of Wyoming highways coupled with the mountainous terrain (i.e., challenging roadway geometry) make the HSM basic SPFs unsuitable to determine crash contributing factors for Wyoming conditions. In this regard, the objective of this study is to implement advanced statistical methods such as the different functional forms of Negative Binomial, and Bayesian approach, to develop crash prediction models, investigate crash contributing factors, and determine the impact of safety countermeasures. Bayesian statistics in combination with the power of Markov Chain Monte Carlo (MCMC) sampling techniques provide frameworks to model small sample datasets and complex models at the same time, where the traditional Maximum Likelihood Estimation (MLE) based methods tend to fail. As such, a novel No-U-Turn Sampler for Hamiltonian Monte Carlo (NUTS HMC) sampling technique in a Bayesian framework was utilized to investigate the crash frequency, injury severity of crashes on the interstate freeways and some rural highways in Wyoming. The Poisson and the Negative Binomial (NB) models are the most commonly used regression models in traffic safety analysis. The advantage of the NB model can be further enhanced by providing different functional forms of the variance and the dispersion structure. The NB-2 is the most common form of the NB model, typically used in developing safety performance functions (SPFs) largely due to the mean-variance quadratic relationship. However, studies in the literature have shown that the mean-variance relationship could be unrestrained. Another introduced formulation of the NB model is NB-1, which assumes that there is a constant ratio linking the mean and the variance of the crash frequencies. A more general type of the NB model is the NB-P model, which does not constrain the mean-variance relationship. Thus, leveraging the power of this unrestrained mean-variance relationship, more accurate safety models could be developed, and these would lead to more accurate estimation of crash risk and benefits of potential solutions. This study will help practitioners to implement advanced methodologies to solve traffic safety problems of rural highways that have plagued the researchers for a long time now. The methodologies proposed in this study will help practitioners to replace the outdated and inefficient traditional models and obtain more accurate traffic safety models to predict crashes and the resulting crash injury severity. Moreover, this research quantified the safety effectiveness of some unique countermeasures on rural highways.

Statistical Methods and Crash Prediction Modeling

Author :
Publisher :
ISBN 13 :
Total Pages : 91 pages
Book Rating : 4.:/5 (279 download)

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Book Synopsis Statistical Methods and Crash Prediction Modeling by :

Download or read book Statistical Methods and Crash Prediction Modeling written by and published by . This book was released on 2006 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Highway and Traffic Safety

Author : National Research Council (U.S.). Transportation Research Board
Publisher :
ISBN 13 :
Total Pages : 148 pages
Book Rating : 4.X/5 (4 download)

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Book Synopsis Highway and Traffic Safety by : National Research Council (U.S.). Transportation Research Board

Download or read book Highway and Traffic Safety written by National Research Council (U.S.). Transportation Research Board and published by . This book was released on 2000 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transportation Research Record contains the following papers: Method for identifying factors contributing to driver-injury severity in traffic crashes (Chen, WH and Jovanis, PP); Crash- and injury-outcome multipliers (Kim, K); Guidelines for identification of hazardous highway curves (Persaud, B, Retting, RA and Lyon, C); Tools to identify safety issues for a corridor safety-improvement program (Breyer, JP); Prediction of risk of wet-pavement accidents : fuzzy logic model (Xiao, J, Kulakowski, BT and El-Gindy, M); Analysis of accident-reduction factors on California state highways (Hanley, KE, Gibby, AR and Ferrara, T); Injury effects of rollovers and events sequence in single-vehicle crashes (Krull, KA, Khattack, AJ and Council, FM); Analytical modeling of driver-guidance schemes with flow variability considerations (Kaysi, I and Ail, NH); Evaluating the effectiveness of Norway's speak out! road safety campaign : The logic of causal inference in road safety evaluation studies (Elvik, R); Effect of speed, flow, and geometric characteristics on crash frequency for two-lane highways (Garber, NJ and Ehrhart, AA); Development of a relational accident database management system for Mexican federal roads (Mendoza, A, Uribe, A, Gil, GZ and Mayoral, E); Estimating traffic accident rates while accounting for traffic-volume estimation error : a Gibbs sampling approach (Davis, GA); Accident prediction models with and without trend : application of the generalized estimating equations procedure (Lord, D and Persaud, BN); Examination of methods that adjust observed traffic volumes on a network (Kikuchi, S, Miljkovic, D and van Zuylen, HJ); Day-to-day travel-time trends and travel-time prediction form loop-detector data (Kwon, JK, Coifman, B and Bickel, P); Heuristic vehicle classification using inductive signatures on freeways (Sun, C and Ritchie, SG).

Traffic Safety Prediction

Author : Houjun Tang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Traffic Safety Prediction by : Houjun Tang

Download or read book Traffic Safety Prediction written by Houjun Tang and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Roadway safety is a high priority among transportation agencies domestically and internationally. In order to improve traffic safety, the research community has been working to develop and apply more advanced statistical modeling methods in an effort to identify relationships between crash frequency or severity and various driver, roadway, and vehicle characteristics. For example, crash frequency models have evolved from Poisson and negative binomial (NB) regression models, to models that handle excess zero counts (e.g., zero-inflated Poisson or NB models), and to models that address unobserved heterogeneity (e.g., latent class and random parameters models). Examples of crash severity models include multinomial, ordered, and nested logit models. These statistical models usually contain assumptions that are not straight-forward to assess, or put limitations on variables and data. To alleviate these concerns, researchers have recently introduced data mining techniques into traffic safety research. Examples of these methods include classification and regression trees (CART), random forests (RF), support vector machines (SVM) and neural networks (NN). Each has shown promising results to predict the frequency or severity of traffic crashes, which is essential to managing the safety performance of a roadway network.Most safety studies that have applied data mining algorithms have focused on model outcomes of specific crash types and have not addressed parameter sensitivity and its influence on model performance. Furthermore, the application of more sophisticated algorithms has been limited in the published traffic safety literature. In light of this, the purpose of the research is to fill these gaps by systematically evaluating the predictive power of CART and RF algorithms in crash severity analysis and the MOB algorithm in a crash frequency context, and by exploring the sensitivity of key parameters that affect model performance within each algorithm. In addition, guidelines for applying select data mining models are generalized for application purposes. Empirical data collected from Pennsylvania are used to accomplish the research tasks. The major findings from this research are as follows: 1. The RF model produced better predictive power than the CART model, while the CART model performed slightly better than the binary logit model, in the crash severity context. 2. When increasing the parameter values in the CART algorithm (i.e., minimum node size and prior probability of fatal and injury crashes), the sensitivity (i.e., prediction accuracy) of fatal and injury crashes increases and the precision decreases.3. The RF model is robust to parameter tuning. The evaluation metrics are stabilized when more than three variables are considered at each node splitting. The model can produce satisfactory performance with limited number of trees (i.e., far less than the default value). The variable importance ranking is not sensitive to different parameter settings.4. The MOB-NB model shows better data fitness than traditional NB models, in terms of log-likelihood and AIC, in the crash frequency context.5. The estimated confidence intervals and elasticities of independent variables suggest that the MOB-NB model can efficiently identify variable effect heterogeneity under different subgroup patterns in the dataset. In the crash frequency context, the existence of passing zones and the posted speed limit were identified as subgroups in the present study.6. The MOB-NB model produces the minimum mean square error among candidate models, including standard NB model and adjusted NB models, which incorporate splitting variables identified by MOB-NB model. The difference in prediction accuracy among the models is relatively small.

Severity Prediction and Time-Series Analysis of Vehicle Accidents Using Statistical Models

Author : Lisa Kaunitz
Publisher :
ISBN 13 :
Total Pages : 47 pages
Book Rating : 4.:/5 (132 download)

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Book Synopsis Severity Prediction and Time-Series Analysis of Vehicle Accidents Using Statistical Models by : Lisa Kaunitz

Download or read book Severity Prediction and Time-Series Analysis of Vehicle Accidents Using Statistical Models written by Lisa Kaunitz and published by . This book was released on 2022 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study explores factors that effect vehicle accidents, predicts the severity of accidents through logistic regression, and forecasts the number of future accidents to occur using time-series analysis. From insights gathered during exploration, a final dataset is prepared for the use of a logistic regression model. The final model predicts whether or not an accident will be severe with an accuracy of 82%, and reveals the three main features that statistically contribute to the odds of an accident having a severe impact on traffic. Finally, a time-series analysis is run in order to model the number of accidents that can occur on a given day using historical data. This paper evaluates the dataset in ways that have yet to be explored, and provides a great baseline understanding of what is possible for the future of transportation.

Statistical Methods and Modeling and Safety Data, Analysis, and Evaluation

Author : National Research Council (U.S.). Transportation Research Board
Publisher :
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.:/5 ( download)

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Book Synopsis Statistical Methods and Modeling and Safety Data, Analysis, and Evaluation by : National Research Council (U.S.). Transportation Research Board

Download or read book Statistical Methods and Modeling and Safety Data, Analysis, and Evaluation written by National Research Council (U.S.). Transportation Research Board and published by . This book was released on 2003 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers empirical approaches to outlier detection in intelligent transportation systems data, modeling of traffic crash-flow relationships for intersections, profiling of high-frequency accident locations by use of association rules, analysis of rollovers and injuries with sport utility vehicles, and automated accident detection at intersections via digital audio signal processing.

Defining New Exposure Measures for Crash Prediction Models by Type of Collision

Author :
Publisher :
ISBN 13 :
Total Pages : 226 pages
Book Rating : 4.:/5 (19 download)

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Book Synopsis Defining New Exposure Measures for Crash Prediction Models by Type of Collision by :

Download or read book Defining New Exposure Measures for Crash Prediction Models by Type of Collision written by and published by . This book was released on 2007 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Analyzing Crash Frequency and Severity Data Using Novel Techniques

Author : Gaurav Satish Mehta
Publisher :
ISBN 13 :
Total Pages : 158 pages
Book Rating : 4.:/5 (94 download)

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Book Synopsis Analyzing Crash Frequency and Severity Data Using Novel Techniques by : Gaurav Satish Mehta

Download or read book Analyzing Crash Frequency and Severity Data Using Novel Techniques written by Gaurav Satish Mehta and published by . This book was released on 2014 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing safe travel from one point to another is the main objective of any public transportation agency. The recent publication of the Highway Safety Manual (HSM) has resulted in an increasing emphasis on the safety performance of specific roadway facilities. The HSM provides tools such as crash prediction models that can be used to make informed decisions. The manual is a good starting point for transportation agencies interested in improving roadway safety in their states. However, the models published in the manual need calibration to account for the local driver behavior and jurisdictional changes. The method provided in the HSM for calibrating crash prediction models is not scientific and has been proved inefficient by several studies. To overcome this limitation this study proposes two alternatives. Firstly, a new method is proposed for calibrating the crash prediction models using negative binomial regression. Secondly, this study investigates new forms of state-specific Safety Performance Function SPFs using negative binomial techniques. The HSM's 1st edition provides a multiplier applied to the univariate crash prediction models to estimate the expected number of crashes for different crash severities. It does not consider the distinct effect unobserved heterogeneity might have on crash severities. To address this limitation, this study developed a multivariate extension of the Conway Maxwell Poisson distribution for predicting crashes. This study gives the statistical properties and the parameter estimation algorithm for the distribution. The last part of this dissertation extends the use of Highway Safety Manual by developing a multivariate crash prediction model for the bridge section of the roads. The study then compares the performance of the newly proposed multivariate Conway Maxwell Poisson (MVCMP) model with the multivariate Poisson Lognormal, univariate Conway Maxwell Poisson (UCMP) and univariate Poisson Lognormal model for different crash severities. This example will help transportation researchers in applying the model correctly.

Analyses of Crash Occurence [sic] and Inury [sic] Severities on Multi Lane Highways Using Machine Learning Algorithms

Author : Abhishek Das
Publisher :
ISBN 13 :
Total Pages : 199 pages
Book Rating : 4.:/5 (67 download)

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Book Synopsis Analyses of Crash Occurence [sic] and Inury [sic] Severities on Multi Lane Highways Using Machine Learning Algorithms by : Abhishek Das

Download or read book Analyses of Crash Occurence [sic] and Inury [sic] Severities on Multi Lane Highways Using Machine Learning Algorithms written by Abhishek Das and published by . This book was released on 2009 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reduction of crash occurrence on the various roadway locations (mid-block segments; signalized intersections; un-signalized intersections) and the mitigation of injury severity in the event of a crash are the major concerns of transportation safety engineers. Multi lane arterial roadways (excluding freeways and expressways) account for forty-three percent of fatal crashes in the state of Florida. Significant contributing causes fall under the broad categories of aggressive driver behavior; adverse weather and environmental conditions; and roadway geometric and traffic factors. The objective of this research was the implementation of innovative, state-of-the-art analytical methods to identify the contributing factors for crashes and injury severity. Advances in computational methods render the use of modern statistical and machine learning algorithms. Even though most of the contributing factors are known a-priori, advanced methods unearth changing trends. Heuristic evolutionary processes such as genetic programming; sophisticated data mining methods like conditional inference tree; and mathematical treatments in the form of sensitivity analyses outline the major contributions in this research. Application of traditional statistical methods like simultaneous ordered probit models, identification and resolution of crash data problems are also key aspects of this study. In order to eliminate the use of unrealistic uniform intersection influence radius of 250 ft, heuristic rules were developed for assigning crashes to roadway segments, signalized intersection and access points using parameters, such as 'site location', 'traffic control' and node information. Use of Conditional Inference Forest instead of Classification and Regression Tree to identify variables of significance for injury severity analysis removed the bias towards the selection of continuous variable or variables with large number of categories. For the injury severity analysis of crashes on highways, the corridors were clustered into four optimum groups. The optimum number of clusters was found using Partitioning around Medoids algorithm. Concepts of evolutionary biology like crossover and mutation were implemented to develop models for classification and regression analyses based on the highest hit rate and minimum error rate, respectively. Low crossover rate and higher mutation reduces the chances of genetic drift and brings in novelty to the model development process. Annual daily traffic; friction coefficient of pavements; on-street parking; curbed medians; surface and shoulder widths; alcohol / drug usage are some of the significant factors that played a role in both crash occurrence and injury severities. Relative sensitivity analyses were used to identify the effect of continuous variables on the variation of crash counts. This study improved the understanding of the significant factors that could play an important role in designing better safety countermeasures on multi lane highways, and hence enhance their safety by reducing the frequency of crashes and severity of injuries. Educating young people about the abuses of alcohol and drugs specifically at high schools and colleges could potentially lead to lower driver aggression. Removal of on-street parking from high speed arterials unilaterally could result in likely drop in the number of crashes. Widening of shoulders could give greater maneuvering space for the drivers. Improving pavement conditions for better friction coefficient will lead to improved crash recovery. Addition of lanes to alleviate problems arising out of increased ADT and restriction of trucks to the slower right lanes on the highways would not only reduce the crash occurrences but also resulted in lower injury severity levels.

Statistical Methods, Safety Data, Analysis, and Evaluation, 2007

Author :
Publisher :
ISBN 13 : 9780309104463
Total Pages : 264 pages
Book Rating : 4.1/5 (44 download)

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Book Synopsis Statistical Methods, Safety Data, Analysis, and Evaluation, 2007 by :

Download or read book Statistical Methods, Safety Data, Analysis, and Evaluation, 2007 written by and published by . This book was released on 2007 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Analysis of Crash Data

Author : Karim El-Basyouny
Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783846535929
Total Pages : 180 pages
Book Rating : 4.5/5 (359 download)

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Book Synopsis Statistical Analysis of Crash Data by : Karim El-Basyouny

Download or read book Statistical Analysis of Crash Data written by Karim El-Basyouny and published by LAP Lambert Academic Publishing. This book was released on 2012 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: While motorized travel provides many benefits, it can also do serious harm in the form of road-related crashes. The problem could be addressed thorough several approaches with engineering initiatives being recognized as the most sustainable and cost effective. Still, the success of the engineering approaches in reducing crash occurrences hinges upon the existence of reliable statistical methods that can provide accurate estimates of safety. However, it was not until recently that advances in statistical modeling techniques have facilitated the fitting of more advanced models to accurately estimate the safety of a road entity. This book, therefore, makes use of these new statistical tools to propose several novel models and methods to analyze crash data. The proposed techniques introduce novel statistical approaches that hold great promise in improving our understanding of the factors that affect the occurrence of crashes. As such, the information in this book should be especially useful to academics and professionals in the traffic safety field, or anyone else who may be interested to know more about the basics, concepts, and emerging methods in crash modeling.

Statistical Methods

Author : National Research Council (U.S.). Transportation Research Board
Publisher :
ISBN 13 :
Total Pages : 254 pages
Book Rating : 4.:/5 ( download)

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Book Synopsis Statistical Methods by : National Research Council (U.S.). Transportation Research Board

Download or read book Statistical Methods written by National Research Council (U.S.). Transportation Research Board and published by . This book was released on 2005 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Transportation Research Record contains 28 papers dealing with statistical methods in highway safety research; highway safety data, analysis, and evaluation; occupant protection; and systematic reviews and meta-analysis. The papers address such topics as risk and crash prediction models, crashes on freeways and at signalized intersections, multivehicle crash prediction, speed and safety, red light running crashes, freeway lane closures, ramp design, accident exposure, rumble strip benefits, collisions with median trees, intersection safety, accident reconstruction, safety effects of speed limit changes, geometric design and head-on crashes, deer-vehicle crashes, sport utility vehicle rollover, vehicle occupancy and crash risk, a logit model for studying injury severity, abdominal injuries in rail passengers, healthy transport policies, and meta-analysis.

Traffic Records, Accident Prediction and Analysis, and Statistical Methods

Author :
Publisher :
ISBN 13 :
Total Pages : 104 pages
Book Rating : 4.X/5 (4 download)

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Book Synopsis Traffic Records, Accident Prediction and Analysis, and Statistical Methods by :

Download or read book Traffic Records, Accident Prediction and Analysis, and Statistical Methods written by and published by . This book was released on 1997 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Transportation Cyber-Physical Systems

Author : Lipika Deka
Publisher : Elsevier
ISBN 13 : 0128142960
Total Pages : 350 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Transportation Cyber-Physical Systems by : Lipika Deka

Download or read book Transportation Cyber-Physical Systems written by Lipika Deka and published by Elsevier. This book was released on 2018-07-30 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transportation Cyber-Physical Systems provides current and future researchers, developers and practitioners with the latest thinking on the emerging interdisciplinary field of Transportation Cyber Physical Systems (TCPS). The book focuses on enhancing efficiency, reducing environmental stress, and meeting societal demands across the continually growing air, water and land transportation needs of both people and goods. Users will find a valuable resource that helps accelerate the research and development of transportation and mobility CPS-driven innovation for the security, reliability and stability of society at-large. The book integrates ideas from Transport and CPS experts and visionaries, consolidating the latest thinking on the topic. As cars, traffic lights and the built environment are becoming connected and augmented with embedded intelligence, it is important to understand how smart ecosystems that encompass hardware, software, and physical components can help sense the changing state of the real world. Bridges the gap between the transportation, CPS and civil engineering communities Includes numerous examples of practical applications that show how diverse technologies and topics are integrated in practice Examines timely, state-of-the-art topics, such as big data analytics, privacy, cybersecurity and smart cities Shows how TCPS can be developed and deployed, along with its associated challenges Includes pedagogical aids, such as Illustrations of application scenarios, architecture details, tables describing available methods and tools, chapter objectives, and a glossary Contains international contributions from academia, government and industry

An Application of Data Analytics to Outcomes of Missouri Motor Vehicle Crashes

Author :
Publisher :
ISBN 13 :
Total Pages : 215 pages
Book Rating : 4.:/5 (919 download)

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Book Synopsis An Application of Data Analytics to Outcomes of Missouri Motor Vehicle Crashes by :

Download or read book An Application of Data Analytics to Outcomes of Missouri Motor Vehicle Crashes written by and published by . This book was released on 2015 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motor vehicle crashes are a leading cause of death in the United States, cost Americans $277 billion annually, and generate serious psychological burdens. As a result, extensive vehicle safety research focusing on the explanatory factors of crash severity is undertaken using a wide array of methodological techniques including traditional statistical models and contemporary data mining approaches. This study advances the methodological frontier of crash severity research by completing an empirical investigation that compares the performance of popular, longstanding techniques of multinomial logit and ordinal probit models with more recent methods of decision tree and artificial neural network models. To further the investigation of the benefits of data analytics, individual models are combined into model ensembles using three popular combinatory techniques. The models are estimated using 2002 to 2012 crash data from the Missouri State Highway Patrol Traffic Division - Statewide Traffic Accident Records System database, and variables examined include various driver characteristics, temporal factors, weather conditions, road characteristics, crash type, crash location, and injury severity levels. The accuracy and discriminatory power of explaining crash severity outcomes among all methods are compared using classification tables, lift charts, ROC curves, and AUC values. The CHAID decision tree model is found to have the greatest accuracy and discriminatory power relative to all evaluated modeling approaches. The modeling reveals that the presence of alcohol, driving at speeds that exceed the limit, failing to yield, driving on the wrong side of the road, violating a stop sign or signal, and driving while physically impaired lead to a large number of fatalities each year. Yet, the effect of these factors on the probability of a severe outcome is dependent upon other variables, including number of occupants involved in the crash, speed limit, lighting condition, and age of the driver. The CHAID decision tree is used in conjunction with prior literature and the current Missouri rules of the road to provide better formulated driving policies. This study concludes that policy makers should consider the interaction of conditions and driver related contributing factors when crafting future legislation or proposing modifications in driving statues.

Safe Mobility

Author : Dominique Lord
Publisher : Emerald Group Publishing
ISBN 13 : 1787148920
Total Pages : 511 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Safe Mobility by : Dominique Lord

Download or read book Safe Mobility written by Dominique Lord and published by Emerald Group Publishing. This book was released on 2018-04-18 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book increases the level of knowledge on road safety contexts, issues and challenges; shares what can currently be done to address the variety of issues; and points to what needs to be done to make further gains in road safety.